Comparison: Data Preparation vs. Inline Data Wrangling in Machine Learning and Deep Learning ProjectsPosted in Analytics, Big Data, Business Intelligence, Hadoop on February 13th, 2017 by Kai Wähner
I want to highlight a new presentation about Data Preparation in Data Science projects:
“Comparison of Programming Languages, Frameworks and Tools for Data Preprocessing and (Inline) Data Wrangling in Machine Learning / Deep Learning Projects”
Data Preparation as Key for Success in Data Science Projects
A key task to create appropriate analytic models in machine learning or deep learning is the integration and preparation of data sets from various sources like files, databases, big data storages, sensors or social networks. This step can take up to 80% of the whole project.